Large Language Models in Bioinformatics: A Survey
Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data.This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling, RNA structure prediction, protein function inference, and single-cell transcriptomics.Meanwhile, we also discuss several key challenges, including data scarcity, computational complexity, and cross-omics integration, and explore future directions such as multimodal learning, hybrid AI models, and clinical applications.By offering a comprehensive perspective, this paper underscores the transformative potential of LLMs in driving innovations in bioinformatics and precision medicine.
Authors
- Jianmin Jiang (ORCID: https://orcid.org/0000-0002-7576-3999)
- Yu Li (ORCID: https://orcid.org/0000-0001-5788-8424)
- Pengan Chen
- Zikang Wang (ORCID: https://orcid.org/0000-0003-1406-1237)
- Zhenyu Wang (ORCID: https://orcid.org/0000-0003-3433-5362)
- Xiangyu Shi (ORCID: https://orcid.org/0000-0002-1496-6194)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.findings-acl.184
- Citations
- 4
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 3.22
Funders
- Innovation and Technology Commission
- Chinese University of Hong Kong